Empowering decision making and accelerating insights in biomedical informatics

Data Quality Analyst – Translational Research

TranslatorTranslatorFull TimeRemoteTeam 51-200Since 1999H1B SponsorCompany Site LinkedIn

Location

United States

Posted

31 days ago

Salary

Not specified

Bachelor DegreeEnglish

Job Description

• Review scientific data submissions for completeness, accuracy, and adherence to defined standards. • Evaluate the consistency and scientific relevance of data and flag potential issues for review. • Assess methodological details of pre-clinical and translational research submissions under the guidance of senior staff. • Support the translation of data workflows into transparent, structured processes that can be adapted for automation and AI-assisted review. • Collaborate with scientific staff, informatics teams, and data providers to resolve discrepancies and improve data quality. • Assist in monitoring data quality metrics and document trends or recurring issues. • Maintain up-to-date knowledge of emerging research methods, data standards, and automation tools to support improvements in data quality practices. • Contribute to team documentation and process refinement efforts as part of continuous improvement initiatives.

Job Requirements

Bachelor’s degree in a relevant scientific or data-related discipline (e.g., biomedical sciences, bioinformatics, epidemiology, virology, immunology, or related field).
Familiarity with pre-clinical research methods and experimental design.
Strong attention to detail with the capacity to identify inconsistencies or gaps in structured scientific data.
Ability to follow established data quality workflows and contribute to process documentation.
Strong written and verbal communication skills, with the ability to summarize findings clearly.
Collaborative mindset, with the willingness to seek guidance and work effectively in a cross-disciplinary team.
Master’s degree in a relevant scientific or data-related field (preferred).
Understanding of controlled vocabularies, ontologies, and biomedical data standards (preferred).
Familiarity with database systems, structured data models, or data submission pipelines (preferred).
Exposure to human-in-the-loop AI processes and automation in data review workflows (preferred).
Experience with quality control, process improvement, or research data management (preferred).